posted on 2003-05-01, 00:00authored byPentti Paatero, Philip K. Hopke, Janjira Hoppenstock, Shelly I. Eberly
This work analyzes PM2.5 24-h average concentrations
measured every third day at over 300 locations in the eastern
United States during 2000. The non-negative factor
analytic model, Positive Matrix Factorization, has been
enhanced by modeling the dependence of PM2.5 concentra
tions on temperature, humidity, pressure, ozone concentrations, and wind velocity vectors. The model comprises 12
general factors, augmented by 5 urban-only factors
intended to represent excess concentration present in
urban locations only. The computed factor components or
concentration fields are displayed as concentration
maps, one for each factor, showing how much each factor
contributes to the average concentration at each location.
The factors are also displayed as flux maps that illustrate
the spatial movement of PM2.5 aerosol, thus enabling one
to pinpoint potential source areas of PM2.5. The quality
of the results was investigated by examining how well the
model reproduces especially high concentrations of
PM2.5 on specific days at specific locations. Delimiting the
spatial extent of all such factors that exhibit a clear
regional maximum surrounded by an almost-zero outer
domain lowered the uncertainty in the computed results.